Structural similarity-based rapid and robust visible light image and SAR image registration method

Abstract

The invention discloses a structural similarity-based rapid and robust visible light image and SAR image registration method. The method comprises the following steps of: firstly carrying out coarse registration on a to-be-registered visible light image and a to-be-registered SAR image by using a rational polynomial coefficient model; carrying out point of interest detection on the visible light image by using an improved corner detection method, and uniformly selecting a certain quantity of points of interest as control points; constructing similarity measurement by using an improved directional Harris corner histogram HIOHC so as to carry out key point matching in the SAR image; after getting rid of obvious mistaken matching, solving a global conversion matrix by using a least square method LSM and obtaining a final registration result. The method has the effects of breaking through dependency, on image descriptors, of traditional methods, breaking through sensitivity, to different data sources, of the traditional methods, obtaining relatively ideal effects, realizing high-precision registration of visible light images and SAR images, and having important practical significance for disaster monitoring, a change detection and loss estimation.

Description

technical field [0001] The invention relates to a registration method for heterogeneous remote sensing images, in particular to a fast and stable registration method for visible light images and SAR images based on structural similarity. Background technique [0002] With the rapid development of geographic information technology, remote sensing sensors have significantly improved both in data quality and characteristics, and more and more remote sensing sensors are installed on remote sensing satellites. According to the method of obtaining information from remote sensing satellites, remote sensing satellites can be briefly divided into two categories, the first is optical sensors that passively receive information, such as GF1, Ikons, etc., and the other is synthetic aperture radar (SAR) sensors that actively acquire information , such as GF3, TerraSAR-X, etc. SAR sensors can emit microwave signals and record signals emitted by the surface, so they can penetrate the inter...

AI Technical Summary

Problems solved by technology

[0005] However, for the registration of visible light images and SAR images, the methods based on MI or PC are relatively slow, and are often not suitable for large-scale remote sensing images, and SAR images have certain changes in brightness and contrast, which lead to the existing registration methods. difficult to achieve desired results

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